Unveiling Cultural Identities and Self Savouring in Preethi Nair’s One Hundred Shades of White and Sarah Addison Allen’s The Girl Who Chased the Moon
Bibliographic record
Abstract
Literature often deals with the notion of self-discovery. Self-realisation is the pinnacle of the inner journey that characters undergo in literature. Different individuals experience it at various stages; some in their adolescence, some in middle life, while others in their later years. Savouring is the act of taking pleasure in and appreciating something, frequently food but also other pursuits like music, nature, and relationships. The ability to savour something correlates with enhanced happiness, health, and contentment in life. Savouring serves as a method of introspection. Discovering oneself, one's ideals, and what provides delight and purpose in life aid in cherishing unique and varied experiences. Thus, this paper attempts to provide a comparative study of two novels, One Hundred Shades of White by Preethi Nair and The Girl Who Chased the Moon by Sarah Addison Allen, in which the female protagonists try to savour their self-discovery through various means, namely food, culture, and identity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.020 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".